Transactive Control of Electric Railways Using Dynamic Market Mechanisms

• Published in: IEEE transactions on control systems technology Vol. 31; no. 2; pp. 748 - 760
• Main Authors: D'Achiardi, David, Annaswamy, Anuradha M., Mazumder, Sudip K., Pilo, Eduardo
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Costs; Distributed generation; Electric power demand; Electric power grids; Electric power systems; Electric railroads; Electricity distribution; Electricity pricing; Energy costs; Energy management; Energy sources; Operating costs; Optimization; Power grid; Power system dynamics; Rail transportation; railway dispatch; Renewable energy sources; renewable integration; Schedules; social welfare; train dispatch; train network; Trains; trajectory optimization; Transactive energy
• ISSN: 1063-6536; 1558-0865
• DOI: 10.1109/TCST.2022.3202171

Electricity demand of electric railways is a relatively unexplored source of flexibility in demand response applications in power systems. In this article, we propose a transactive control-based optimization framework for coordinating the power grid network and the train network. This is accomplished by coordinating dispatchable distributed energy resources (DERs) and demand profiles of trains using a two-step optimization. A railway-based dynamic market mechanism (rDMM) is proposed for the dispatch of DERs in the power network along the electric railway using an iterative negotiation process, generates the profiles of electricity prices, and constitutes the first step. The train dispatch attempts to minimize the operational costs of trains that ply along the railway, while subject to constraints on their acceleration profiles, route schedules, and the train dynamics, and generate demand profiles of trains and constitute the second step. The rDMM seeks to optimize the operational costs of the underlying DERs while ensuring power balance. Together, they form an overall framework that yields the desired transactions between the railway and power grid infrastructures. This overall optimization approach is validated using simulation studies of the Southbound Amtrak service along the Northeast Corridor (NEC) in USA, which shows a 25% reduction in energy costs when compared to standard trip optimization based on minimum work and a 75% reduction in energy costs when compared to the train cost calculated using a field dataset.